Pandas Profiling Report

Dataset statistics

Number of variables	17
Number of observations	54881
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	7.1 MiB
Average record size in memory	136.0 B

Variable types

Numeric	9
Categorical	8

Alerts

`df_index` is highly correlated with `id`	High correlation
`id` is highly correlated with `df_index`	High correlation
`weight` is highly correlated with `bmi` and 1 other fields	High correlation
`ap_hi` is highly correlated with `ap_lo` and 2 other fields	High correlation
`ap_lo` is highly correlated with `ap_hi` and 1 other fields	High correlation
`bmi` is highly correlated with `weight` and 1 other fields	High correlation
`bmi_class` is highly correlated with `weight` and 1 other fields	High correlation
`bp_class` is highly correlated with `ap_hi` and 1 other fields	High correlation
`gender` is highly correlated with `smoke`	High correlation
`height` is highly correlated with `gender`	High correlation
`cholesterol` is highly correlated with `gluc`	High correlation
`gluc` is highly correlated with `cholesterol`	High correlation
`smoke` is highly correlated with `gender` and 1 other fields	High correlation
`alco` is highly correlated with `smoke`	High correlation
`cardio` is highly correlated with `ap_hi`	High correlation
`df_index` is uniformly distributed	Uniform
`id` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`id` has unique values	Unique
`bmi_class` has 3863 (7.0%) zeros	Zeros

Reproduction

Analysis started	2022-12-09 10:19:34.585624
Analysis finished	2022-12-09 10:19:56.401299
Duration	21.82 seconds
Software version	pandas-profiling v3.4.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	54881
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	34991.71881

Minimum	0
Maximum	69999
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	0
5-th percentile	3512
Q1	17472
median	34954
Q3	52537
95-th percentile	66522
Maximum	69999
Range	69999
Interquartile range (IQR)	35065

Descriptive statistics

Standard deviation	20217.69519
Coefficient of variation (CV)	0.5777851412
Kurtosis	-1.201013232
Mean	34991.71881
Median Absolute Deviation (MAD)	17531
Skewness	0.002483918404
Sum	1920380520
Variance	408755198.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
47339	1	< 0.1%
29190	1	< 0.1%
66473	1	< 0.1%
5892	1	< 0.1%
58823	1	< 0.1%
65067	1	< 0.1%
49192	1	< 0.1%
61559	1	< 0.1%
21587	1	< 0.1%
62428	1	< 0.1%
Other values (54871)	54871	> 99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
69999	1	< 0.1%
69998	1	< 0.1%
69997	1	< 0.1%
69996	1	< 0.1%
69994	1	< 0.1%
69993	1	< 0.1%
69992	1	< 0.1%
69991	1	< 0.1%
69990	1	< 0.1%
69989	1	< 0.1%

id
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	54881
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49961.32993

Minimum	0
Maximum	99999
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	0
5-th percentile	4976
Q1	24965
median	49928
Q3	74943
95-th percentile	94969
Maximum	99999
Range	99999
Interquartile range (IQR)	49978

Descriptive statistics

Standard deviation	28865.97933
Coefficient of variation (CV)	0.5777664319
Kurtosis	-1.199381969
Mean	49961.32993
Median Absolute Deviation (MAD)	24987
Skewness	0.001210067816
Sum	2741927748
Variance	833244762.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
67617	1	< 0.1%
41703	1	< 0.1%
94898	1	< 0.1%
8366	1	< 0.1%
83956	1	< 0.1%
92870	1	< 0.1%
70227	1	< 0.1%
87891	1	< 0.1%
30836	1	< 0.1%
89148	1	< 0.1%
Other values (54871)	54871	> 99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
12	1	< 0.1%
13	1	< 0.1%
14	1	< 0.1%
15	1	< 0.1%

Value	Count	Frequency (%)
99999	1	< 0.1%
99998	1	< 0.1%
99996	1	< 0.1%
99995	1	< 0.1%
99992	1	< 0.1%
99991	1	< 0.1%
99990	1	< 0.1%
99988	1	< 0.1%
99986	1	< 0.1%
99985	1	< 0.1%

age
Real number (ℝ_≥0)

Distinct	28
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	52.81468997

Minimum	29
Maximum	64
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	29
5-th percentile	41
Q1	48
median	53
Q3	58
95-th percentile	63
Maximum	64
Range	35
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.775996528
Coefficient of variation (CV)	0.1282975728
Kurtosis	-0.8208755654
Mean	52.81468997
Median Absolute Deviation (MAD)	5
Skewness	-0.3020382886
Sum	2898523
Variance	45.91412895
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
55	3091	5.6%
53	3049	5.6%
57	2836	5.2%
59	2829	5.2%
54	2820	5.1%
56	2819	5.1%
49	2696	4.9%
58	2644	4.8%
51	2610	4.8%
52	2599	4.7%
Other values (18)	26888	49.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
29	3	< 0.1%
30	1	< 0.1%
39	1412	2.6%
40	1300	2.4%
41	1510	2.8%
42	1094	2.0%
43	1593	2.9%
44	1195	2.2%
45	1630	3.0%
46	1285	2.3%

Value	Count	Frequency (%)
64	1723	3.1%
63	2132	3.9%
62	1736	3.2%
61	2099	3.8%
60	2496	4.5%
59	2829	5.2%
58	2644	4.8%
57	2836	5.2%
56	2819	5.1%
55	3091	5.6%

gender
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

1	35711
2	19170

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	2
3rd row	2
4th row	2
5th row	1

Common Values

Value	Count	Frequency (%)
1	35711	65.1%
2	19170	34.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	35711	65.1%
2	19170	34.9%

Most occurring characters

Value	Count	Frequency (%)
1	35711	65.1%
2	19170	34.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	35711	65.1%
2	19170	34.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	35711	65.1%
2	19170	34.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	35711	65.1%
2	19170	34.9%

height
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	84
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	164.3915927

Minimum	100
Maximum	250
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	100
5-th percentile	152
Q1	159
median	165
Q3	170
95-th percentile	178
Maximum	250
Range	150
Interquartile range (IQR)	11

Descriptive statistics

Standard deviation	7.96864217
Coefficient of variation (CV)	0.04847353833
Kurtosis	1.526689503
Mean	164.3915927
Median Absolute Deviation (MAD)	5
Skewness	-0.05029660799
Sum	9021975
Variance	63.49925803
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
165	4581	8.3%
160	3990	7.3%
170	3674	6.7%
168	3436	6.3%
164	2672	4.9%
158	2567	4.7%
162	2564	4.7%
169	2200	4.0%
156	2196	4.0%
163	2028	3.7%
Other values (74)	24973	45.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
100	2	< 0.1%
104	2	< 0.1%
105	2	< 0.1%
108	1	< 0.1%
109	1	< 0.1%
110	6	< 0.1%
111	1	< 0.1%
112	1	< 0.1%
113	1	< 0.1%
117	2	< 0.1%

Value	Count	Frequency (%)
250	1	< 0.1%
207	1	< 0.1%
198	10	< 0.1%
197	4	< 0.1%
196	6	< 0.1%
195	5	< 0.1%
194	1	< 0.1%
193	6	< 0.1%
192	9	< 0.1%
191	7	< 0.1%

weight
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	240
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	74.12450538

Minimum	40
Maximum	200
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	40
5-th percentile	55
Q1	65
median	72
Q3	82
95-th percentile	100
Maximum	200
Range	160
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	14.25051388
Coefficient of variation (CV)	0.1922510485
Kurtosis	2.559568857
Mean	74.12450538
Median Absolute Deviation (MAD)	8
Skewness	1.018748821
Sum	4068026.98
Variance	203.0771459
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
65	3037	5.5%
70	2988	5.4%
68	2209	4.0%
60	2152	3.9%
75	2114	3.9%
80	2103	3.8%
72	1783	3.2%
69	1695	3.1%
78	1639	3.0%
62	1471	2.7%
Other values (230)	33690	61.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
40	31	0.1%
41	30	0.1%
42	34	0.1%
42.2	1	< 0.1%
43	50	0.1%
44	50	0.1%
45	100	0.2%
46	76	0.1%
47	89	0.2%
48	133	0.2%

Value	Count	Frequency (%)
200	2	< 0.1%
180	4	< 0.1%
178	2	< 0.1%
172	1	< 0.1%
171	1	< 0.1%
170	2	< 0.1%
169	1	< 0.1%
168	2	< 0.1%
167	2	< 0.1%
166	2	< 0.1%

ap_hi
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	97
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	126.5520854

Minimum	80
Maximum	200
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	80
5-th percentile	100
Q1	120
median	120
Q3	140
95-th percentile	160
Maximum	200
Range	120
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	16.53810059
Coefficient of variation (CV)	0.1306821657
Kurtosis	1.317943987
Mean	126.5520854
Median Absolute Deviation (MAD)	10
Skewness	0.833832394
Sum	6945305
Variance	273.5087712
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
120	22142	40.3%
140	7462	13.6%
130	7102	12.9%
110	6870	12.5%
150	3350	6.1%
160	2214	4.0%
100	2073	3.8%
90	785	1.4%
170	521	0.9%
180	490	0.9%
Other values (87)	1872	3.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
80	76	0.1%
85	7	< 0.1%
90	785	1.4%
93	1	< 0.1%
95	28	0.1%
96	2	< 0.1%
97	1	< 0.1%
99	2	< 0.1%
100	2073	3.8%
101	4	< 0.1%

Value	Count	Frequency (%)
200	77	0.1%
197	1	< 0.1%
195	1	< 0.1%
193	2	< 0.1%
191	2	< 0.1%
190	91	0.2%
188	1	< 0.1%
185	7	< 0.1%
180	490	0.9%
179	4	< 0.1%

ap_lo
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	75
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	81.32477542

Minimum	50
Maximum	140
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	50
5-th percentile	70
Q1	80
median	80
Q3	90
95-th percentile	100
Maximum	140
Range	90
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	9.444009087
Coefficient of variation (CV)	0.1161270847
Kurtosis	1.794702921
Mean	81.32477542
Median Absolute Deviation (MAD)	0
Skewness	0.3894453676
Sum	4463185
Variance	89.18930763
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
80	27815	50.7%
90	11381	20.7%
70	8134	14.8%
100	3245	5.9%
60	2177	4.0%
110	297	0.5%
79	295	0.5%
85	235	0.4%
75	177	0.3%
120	148	0.3%
Other values (65)	977	1.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
50	43	0.1%
52	2	< 0.1%
53	3	< 0.1%
54	1	< 0.1%
55	4	< 0.1%
56	1	< 0.1%
57	3	< 0.1%
58	4	< 0.1%
59	15	< 0.1%
60	2177	4.0%

Value	Count	Frequency (%)
140	21	< 0.1%
135	1	< 0.1%
130	24	< 0.1%
126	1	< 0.1%
125	2	< 0.1%
122	1	< 0.1%
121	1	< 0.1%
120	148	0.3%
119	2	< 0.1%
118	1	< 0.1%

cholesterol
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

1	41169
2	7455
3	6257

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	41169	75.0%
2	7455	13.6%
3	6257	11.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	41169	75.0%
2	7455	13.6%
3	6257	11.4%

Most occurring characters

Value	Count	Frequency (%)
1	41169	75.0%
2	7455	13.6%
3	6257	11.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	41169	75.0%
2	7455	13.6%
3	6257	11.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	41169	75.0%
2	7455	13.6%
3	6257	11.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	41169	75.0%
2	7455	13.6%
3	6257	11.4%

gluc
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

1	46704
3	4116
2	4061

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	46704	85.1%
3	4116	7.5%
2	4061	7.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	46704	85.1%
3	4116	7.5%
2	4061	7.4%

Most occurring characters

Value	Count	Frequency (%)
1	46704	85.1%
3	4116	7.5%
2	4061	7.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	46704	85.1%
3	4116	7.5%
2	4061	7.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	46704	85.1%
3	4116	7.5%
2	4061	7.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	46704	85.1%
3	4116	7.5%
2	4061	7.4%

smoke
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

0	50014
1	4867

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	50014	91.1%
1	4867	8.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	50014	91.1%
1	4867	8.9%

Most occurring characters

Value	Count	Frequency (%)
0	50014	91.1%
1	4867	8.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	50014	91.1%
1	4867	8.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	50014	91.1%
1	4867	8.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	50014	91.1%
1	4867	8.9%

alco
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

0	51885
1	2996

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	51885	94.5%
1	2996	5.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	51885	94.5%
1	2996	5.5%

Most occurring characters

Value	Count	Frequency (%)
0	51885	94.5%
1	2996	5.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	51885	94.5%
1	2996	5.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	51885	94.5%
1	2996	5.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	51885	94.5%
1	2996	5.5%

active
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

1	44093
0	10788

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	44093	80.3%
0	10788	19.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	44093	80.3%
0	10788	19.7%

Most occurring characters

Value	Count	Frequency (%)
1	44093	80.3%
0	10788	19.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	44093	80.3%
0	10788	19.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	44093	80.3%
0	10788	19.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	44093	80.3%
0	10788	19.7%

bp_class
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

2	31832
3	12802
0	7595
1	2510
4	142

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	3
3rd row	3
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	31832	58.0%
3	12802	23.3%
0	7595	13.8%
1	2510	4.6%
4	142	0.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
2	31832	58.0%
3	12802	23.3%
0	7595	13.8%
1	2510	4.6%
4	142	0.3%

Most occurring characters

Value	Count	Frequency (%)
2	31832	58.0%
3	12802	23.3%
0	7595	13.8%
1	2510	4.6%
4	142	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	31832	58.0%
3	12802	23.3%
0	7595	13.8%
1	2510	4.6%
4	142	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	31832	58.0%
3	12802	23.3%
0	7595	13.8%
1	2510	4.6%
4	142	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	31832	58.0%
3	12802	23.3%
0	7595	13.8%
1	2510	4.6%
4	142	0.3%

bmi
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	2093
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.68094386

Minimum	12.14
Maximum	80.24
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	12.14
5-th percentile	18.04
Q1	20.71
median	22.9
Q3	26.03
95-th percentile	31.78
Maximum	80.24
Range	68.1
Interquartile range (IQR)	5.32

Descriptive statistics

Standard deviation	4.385587751
Coefficient of variation (CV)	0.1851948038
Kurtosis	4.273553907
Mean	23.68094386
Median Absolute Deviation (MAD)	2.55
Skewness	1.257398333
Sum	1299633.88
Variance	19.23337993
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
20.71	748	1.4%
19.79	522	1.0%
21.55	503	0.9%
22.3	404	0.7%
21.85	370	0.7%
22.16	354	0.6%
19.12	341	0.6%
23.09	340	0.6%
22.78	332	0.6%
20.07	324	0.6%
Other values (2083)	50643	92.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
12.14	1	< 0.1%
12.75	1	< 0.1%
12.88	2	< 0.1%
13.02	1	< 0.1%
13.1	1	< 0.1%
13.16	1	< 0.1%
13.26	1	< 0.1%
13.29	3	< 0.1%
13.38	3	< 0.1%
13.47	3	< 0.1%

Value	Count	Frequency (%)
80.24	1	< 0.1%
77.33	1	< 0.1%
76.84	1	< 0.1%
70.21	1	< 0.1%
69.11	1	< 0.1%
62.29	1	< 0.1%
57.43	1	< 0.1%
56.72	2	< 0.1%
55.71	1	< 0.1%
55.67	1	< 0.1%

bmi_class
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.353073013

Minimum	0
Maximum	5
Zeros	3863
Zeros (%)	7.0%
Negative	0
Negative (%)	0.0%
Memory size	428.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	2
95-th percentile	3
Maximum	5
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.7988181895
Coefficient of variation (CV)	0.5903733074
Kurtosis	2.510469159
Mean	1.353073013
Median Absolute Deviation (MAD)	0
Skewness	1.237117311
Sum	74258
Variance	0.6381104999
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	33657	61.3%
2	12738	23.2%
0	3863	7.0%
3	3611	6.6%
4	768	1.4%
5	244	0.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	3863	7.0%
1	33657	61.3%
2	12738	23.2%
3	3611	6.6%
4	768	1.4%
5	244	0.4%

Value	Count	Frequency (%)
5	244	0.4%
4	768	1.4%
3	3611	6.6%
2	12738	23.2%
1	33657	61.3%
0	3863	7.0%

cardio
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	428.9 KiB

0	27738
1	27143

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	54881
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	27738	50.5%
1	27143	49.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	27738	50.5%
1	27143	49.5%

Most occurring characters

Value	Count	Frequency (%)
0	27738	50.5%
1	27143	49.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	54881	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	27738	50.5%
1	27143	49.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	54881	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	27738	50.5%
1	27143	49.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54881	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	27738	50.5%
1	27143	49.5%

Auto

The auto setting is an easily interpretable pairwise column metric of the following mapping: vartype-vartype : method, categorical-categorical : Cramer's V, numerical-categorical : Cramer's V (using a discretized numerical column), numerical-numerical : Spearman's ρ. This configuration uses the best suitable for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	id	age	gender	height	weight	ap_hi	ap_lo	cholesterol	gluc	active	bp_class	bmi	bmi_class	cardio
0	47339	67617	59	1	154	80.0	130	90	2	1	1	2	27.51	2	1
1	67456	96320	45	2	162	70.0	140	90	1	1	0	3	22.77	1	1
2	12308	17571	57	2	174	92.0	150	100	1	1	1	3	27.54	2	1
3	32557	46492	64	2	173	76.0	120	82	1	1	1	2	22.91	1	1
4	664	945	55	1	160	60.0	120	80	1	1	1	2	19.79	1	0
5	21003	29995	59	1	156	120.0	120	80	3	2	1	2	40.70	5	1
6	29637	42373	50	2	179	87.0	110	80	1	1	1	2	25.16	2	0
7	57937	82685	63	1	168	79.0	150	90	1	1	1	3	24.65	1	1
8	23680	33853	55	2	180	103.0	120	80	3	1	1	2	29.58	2	1
9	26306	37576	63	2	166	70.0	120	80	1	1	1	2	22.15	1	1

Last rows

	df_index	id	age	gender	height	weight	ap_hi	ap_lo	cholesterol	gluc	smoke	active	bp_class	bmi	bmi_class	cardio
54871	67221	95976	40	1	150	54.0	110	60	1	1	0	1	0	19.09	1	0
54872	41090	58719	40	1	146	47.0	110	80	1	1	0	1	2	17.08	0	0
54873	16023	22883	40	1	169	63.0	120	80	1	1	0	1	2	19.53	1	0
54874	60263	86039	50	1	162	83.0	130	90	3	1	0	1	2	27.00	2	0
54875	44131	63047	53	1	169	61.0	170	90	2	2	0	0	3	18.91	1	1
54876	37194	53137	43	2	170	75.0	150	80	1	1	1	1	2	23.08	1	1
54877	6265	8918	63	2	162	73.0	160	90	1	1	0	1	3	23.75	1	1
54878	54886	78302	64	1	169	74.0	120	80	1	1	0	1	2	22.93	1	0
54879	860	1197	49	1	167	70.0	120	80	1	1	0	0	2	22.00	1	0
54880	15795	22556	41	2	177	64.0	120	80	1	1	0	1	2	18.77	1	0

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII